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About This Role
About CWILL CWILL (pronounced 'quill') is a post-purchase and retention suite built for Shopify brands. Reduce support tickets, recover lost revenue from returns, and turn one-time buyers into loyal fans — with tools purpose-built for every touchpoint that follows the sale.
About the Role CWILL AI SEO & Image Optimizer is our AI-powered SEO and site speed product for cross-border e-commerce and Shopify merchants. It helps merchants improve content quality, indexing, keyword coverage and organic traffic, with more site audits, keyword analysis, content generation, reporting and AI SEO workflows on the way.
As an R&D Trainee, you'll learn by building real features with a mentor, and grow into an engineer who owns a module independently.
Product Intro:
https://www.cwill.com/products/seo-speed/
Base location required:
Cary, NC
(We are unable to hire in other states; relocation will be required.)
Hybrid remote working setting
What You'll DoBuild AI SEO Features
- With guidance from your mentor, develop features across site audits, page checks, keyword analysis, content optimization, AI suggestions and reporting
- Break down requirements into technical tasks, then code, integrate, test and release
- Work on API integration between frontend and backend, data processing, business logic and UI improvements
- Own the quality of what you ship
Process SEO Data and Improve the System
- Work with page, keyword, meta tag, site structure and indexing data
- Build SEO check rules, scoring logic, optimization suggestions and report metrics
- Help troubleshoot production bugs, data issues and customer-reported problems
Build AI SEO Capabilities
- Develop AI generation of titles, meta descriptions, content suggestions and keyword suggestions
- Improve AI output quality, generation speed, user experience and error handling
- Work on prompts, rules, templates and output evaluation
Collaborate and Deliver
- Work with product, design, QA, operations and customer success to understand the why behind each feature
- Follow team coding standards, take part in code review, and add documentation and tests
- Share progress, risks and blockers proactively, and join retrospectives after each launch
Your Growth Path
- By 3 months: understand the product and its main workflows; complete small features, bug fixes and data tasks with your mentor
- By 6 months: independently own a small module, such as an SEO check, optimization suggestions or a report page
- By 12 months: own a product module or technical area at the level of a junior engineer
Requirements Requirements
- Proficiency in Go (Golang) is required. Experience with other languages such as JavaScript/TypeScript, Python, Java or PHP is a plus
- Bachelor's or master's degree from a US university, graduating recently or within the last 1–2 years. Any major; Computer Science, Information Systems, Engineering or related fields preferred
- Solid understanding of web development fundamentals: HTTP, APIs, databases and frontend–backend interaction
- Good coding and debugging skills: you can get to the bottom of a problem and fix it completely
- Strong learner who reads documentation, digs into problems and grows quickly on real projects
- Reliable and detail-oriented; you keep the team updated on progress and issues
- Professional working proficiency in Mandarin Chinese and English (you will work daily with our engineering team in China)
- Software development or SaaS internship experience preferred
Nice to Have
- Experience building web apps, SaaS, SEO tools, AI apps, online stores or Shopify apps
- Familiarity with one or more of: PHP, React, Node.js, Next.js, NestJS, Python, PostgreSQL, Redis
- Basic SEO knowledge: keywords, titles, meta descriptions, site structure, indexing and organic traffic
- AI projects such as LLM apps, prompting, RAG, content generation or automated analysis
- Experience with data collection, data cleaning, reporting or web crawlers
Benefits
Starting Pay: 80k - 110k depends on experiences, open to negotiation
- 401(k)
- PTO
- Paid Holidays
- Insurance
Salary Context
This $80K-$110K range is in the lower quartile for AI Software Engineer roles in our dataset (median: $192K across 198 roles with salary data).
Role Details
About This Role
AI Software Engineers build the applications and systems that AI models run inside. They own the API layers, data pipelines, frontend integrations, and infrastructure that turn a model into a product users interact with. Every AI company needs engineers who can build the software around the AI.
The challenge is building reliable systems around inherently unreliable components. Models are probabilistic. They'll give different answers to the same question. They hallucinate. They're slow. They're expensive. Your job is to build an application layer that handles all of this gracefully while delivering a product that users trust and enjoy.
Across the 9,079 AI roles we're tracking, AI Software Engineer positions make up 5% of the market. At Cwill, this role fits into their broader AI and engineering organization.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
What the Work Looks Like
A typical week includes: building API endpoints that serve model inference with caching and fallback logic, designing the data pipeline that feeds context to a RAG system, implementing streaming responses in the frontend, debugging a race condition in the async inference pipeline, and optimizing database queries for the vector search layer. It's full-stack engineering with AI at the center.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
Skills Required
Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.
Knowledge of vector databases, embedding APIs, and LLM integration patterns (function calling, structured outputs, retry logic) differentiates AI software engineers from general software engineers. Understanding cost optimization (caching strategies, model routing, batched inference) is valuable since inference costs can dominate application economics.
Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
Compensation Benchmarks
AI Software Engineer roles pay a median of $220,000 based on 1,601 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($95K) sits 57% below the category median. Disclosed range: $80K to $110K.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
Cwill AI Hiring
Cwill has 4 open AI roles right now. They're hiring across AI Software Engineer, AI/ML Engineer. Based in Cary, NC, US. Compensation range: $85K - $110K.
Location Context
Across all AI roles, 6% (531 positions) offer remote work, while 8,478 require on-site attendance. Top AI hiring metros: New York (3,078 roles, $221,000 median); San Francisco (2,646 roles, $261,000 median); Los Angeles (1,486 roles, $210,000 median).
Career Path
Common paths into AI Software Engineer roles include Software Engineer, Full-Stack Developer, Backend Engineer.
From here, career progression typically leads toward Staff Engineer, AI Architect, Engineering Manager.
If you're a software engineer, you're already 80% there. Learn the AI integration patterns: RAG, streaming inference, function calling, structured outputs. Build a project that demonstrates you can wrap an AI model in a production-quality application with proper error handling, caching, and user experience. That's the portfolio piece that gets you hired.
What to Expect in Interviews
Technical screens look like standard software engineering interviews with an AI twist. Expect system design questions about building reliable applications around probabilistic models: handling streaming responses, implementing retry logic for API failures, and designing caching strategies for LLM outputs. Coding rounds test standard algorithms plus practical integration patterns like async processing and rate limiting.
When evaluating opportunities: Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
AI Hiring Overview
The AI job market has 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 roles).
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
The AI Job Market Today
The AI job market spans 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (106) are outnumbered by mid-level (4,384) and senior (3,343) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $256,000 median, while Prompt Engineer roles sit at $141,440. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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